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ECML
2007
Springer
14 years 1 months ago
Dual Strategy Active Learning
Abstract. Active Learning methods rely on static strategies for sampling unlabeled point(s). These strategies range from uncertainty sampling and density estimation to multi-factor...
Pinar Donmez, Jaime G. Carbonell, Paul N. Bennett
BILDMED
2008
147views Algorithms» more  BILDMED 2008»
13 years 9 months ago
Automatic Liver Segmentation Using the Random Walker Algorithm
In this paper we present a new method for fully automatic liver segmentation in computed tomography images. First, an initial set of seed points for the random walker algorithm is ...
Florian Maier, Andreas Wimmer, Grzegorz Soza, Jens...
DMIN
2007
226views Data Mining» more  DMIN 2007»
13 years 9 months ago
Generative Oversampling for Mining Imbalanced Datasets
— One way to handle data mining problems where class prior probabilities and/or misclassification costs between classes are highly unequal is to resample the data until a new, d...
Alexander Liu, Joydeep Ghosh, Cheryl Martin
ICASSP
2010
IEEE
13 years 7 months ago
Fixed-budget kernel recursive least-squares
We present a kernel-based recursive least-squares (KRLS) algorithm on a fixed memory budget, capable of recursively learning a nonlinear mapping and tracking changes over time. I...
Steven Van Vaerenbergh, Ignacio Santamaría,...
JMLR
2006
108views more  JMLR 2006»
13 years 7 months ago
Learning Spectral Clustering, With Application To Speech Separation
Spectral clustering refers to a class of techniques which rely on the eigenstructure of a similarity matrix to partition points into disjoint clusters, with points in the same clu...
Francis R. Bach, Michael I. Jordan